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103 Results

Estimating Policy Functions in Payments Systems Using Reinforcement Learning

We demonstrate the ability of reinforcement learning techniques to estimate the best-response functions of banks participating in high-value payments systems—a real-world strategic game of incomplete information.

Eggs in One Basket: Security and Convenience of Digital Currencies

Staff Working Paper 2021-6 Charles M. Kahn, Francisco Rivadeneyra, Tsz-Nga Wong
Digital currencies store balances in anonymous electronic addresses. This paper analyzes the trade-offs between the safety and convenience of aggregating balances in addresses, electronic wallets and banks.

Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19

Staff Working Paper 2021-2 James Chapman, Ajit Desai
We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.

Safe Payments

In a cashless economy, would the private sector invest in the optimal level of safety in a deposit-based payment system? In general, because of externalities, the answer is no. While the private sector could over- or under-invest in safety, the government can use taxes or subsidies to correct private incentives.

Security and convenience of a central bank digital currency

Staff Analytical Note 2020-21 Charles M. Kahn, Francisco Rivadeneyra
An anonymous token-based central bank digital currency (CBDC) would pose certain security risks to users. These risks arise from how balances are aggregated, from their transactional use and from the competition between suppliers of aggregation solutions.

Predicting Payment Migration in Canada

Staff Working Paper 2020-37 Anneke Kosse, Zhentong Lu, Gabriel Xerri
Developments are underway to replace Canada’s two core payment systems with three new systems. We use a discrete choice model to predict migration patterns of end-users and financial institutions for future systems and discuss their policy implications.

What do high-frequency expenditure network data reveal about spending and inflation during COVID‑19?

Staff Analytical Note 2020-20 Kim Huynh, Helen Lao, Patrick Sabourin, Angelika Welte
The official consumer price index (CPI) inflation measure, based on a fixed basket set before the COVID 19 pandemic, may not fully reflect what consumers are currently experiencing. We partnered with Statistics Canada to construct a more representative index for the pandemic with weights based on real-time transaction and survey data.

Liquidity Usage and Payment Delay Estimates of the New Canadian High Value Payments System

Staff Discussion Paper 2020-9 Francisco Rivadeneyra, Nellie Zhang
As part of modernizing its core payments infrastructure, Canada will replace the Large Value Transfer System (LVTS) with a new Real-Time Gross Settlement (RTGS) system called Lynx. An important question for policy-makers is how Lynx should be designed.

Survival Analysis of Bank Note Circulation: Fitness, Network Structure and Machine Learning

Staff Working Paper 2020-33 Diego Rojas, Juan Estrada, Kim Huynh, David T. Jacho-Chávez
Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash.

Monetary Policy Implementation and Payment System Modernization

Staff Working Paper 2020-26 Jonathan Witmer
Canada plans to adopt a retail payment system to allow Canadians to pay in real time (or near real time) 24 hours a day, 7 days a week. However, the traditional model for setting the overnight interest rate does not operate 24/7.
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